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README.md

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 ## Dataset Summary
 
-WikiMusicText (WikiMT) is a new dataset comprising 1010 lead sheets in ABC notation sourced from Wikifonia.org, accompanied by a title, artist, genre, and description. The dataset covers eight genres and is intended for evaluating semantic search and music classification. The data was collected by converting MusicXML sheet music to ABC notation, extracting title and artist names, crawling corresponding Wikipedia entries, assigning genre labels based on the most frequent genre keywords, and summarizing the entries using BART-large. The dataset includes only publicly available music, but users should exercise caution when using it. WikiMT offers a unique resource for music-related natural language processing research, but further investigation is needed to explore potential biases and limitations of the dataset.
+In [CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval](https://ai-muzic.github.io/clamp/), we introduce WikiMusicText (WikiMT), a new dataset for the evaluation of semantic search and music classification. It includes 1010 lead sheets in ABC notation sourced from Wikifonia.org, each accompanied by a title, artist, genre, and description. The title and artist information is extracted from the score, whereas the genre labels are obtained by matching keywords from the Wikipedia entries and assigned to one of the 8 classes (Jazz, Country, Folk, R&B, Pop, Rock, Dance, and Latin) that loosely mimic the GTZAN genres. The description is obtained by utilizing BART-large to summarize and clean the corresponding Wikipedia entry. Additionally, the natural language information within the ABC notation is removed.
 
 ## Copyright Disclaimer
 WikiMT was curated from publicly available sources and is believed to be in the public domain. However, it is important to acknowledge that copyright issues cannot be entirely ruled out. Therefore, users of the dataset should exercise caution when using it. The authors of WikiMT do not assume any legal responsibility for the use of the dataset. If you have any questions or concerns regarding the dataset's copyright status, please contact the authors at shangda@mail.ccom.edu.cn.